14.1- Predicting Breeding Value 2

Estimating Breeding Value

Breeding Value (BV)

• Genetic merit of an animal for a given trait.

• Often expressed as a deviation from herd or group average.

Breeding Value (BV)

• In real life we observe the phenotype but want to estimate the breeding value (or its genetic additive effect)

Breeding Value (BV)

• We observed that the phenotype of a given animal is 630 lbs at Weaning

• But what is its breeding value (i.e. values of its genes to its offspring)?

Some DefinitionsPredicting Genetic Gain

• Breeding Value (BV): The value of an animal as a (genetic) parent.

• Breeding Value: The part of an individual genotypic value that is due to additive effect and therefore transmittable. (Breed true)

• Independent Gene Effect: The effect of an allele is independent of the effect of the other allele at the same locus (dominance) and the effects of alleles at other loci (epistasis). ADDITIVE EFFECT.

• Estimated Breeding Value (EBV): An estimation of a breeding Value.

Some DefinitionsPredicting Genetic Gain

• Independent Gene Effect: The effect of an allele is independent of the effect of the other allele at the same locus (dominance) and the effects of alleles at other loci (epistasis). ADDITIVE EFFECT.

• Estimated Breeding Value (EBV): An estimation of a breeding Value.

• Additive Genetic Value = Breeding Value.

• “Breed True" (i.e., average offspring performance closely approximates average parent performance assuming constant environment)

Genotypic Value is not the same as

Breeding Value

• Genotypic Value of an animal is the value of its genes on itself and includes Additive, Dominant and Epistatic Effects.

• Breeding Value is the value of its genes on the progeny and is related to the Additive Effects (Breed True and narrow sense heritability)

Progeny Differences

• Progeny Difference (PD) or Transmitting Ability (TA): Half of an individual’s breeding value. The expected difference of the individual’s progeny and the mean performance of all progenies.

• Expected Progeny Difference (EPD) or Predicted Transmitting Ability (PTA): A prediction of a progeny difference.

Expected Progeny Difference (EPD) or Predicted Transmitting Ability (PTA):

The expected difference of the individual’s progeny and the mean

performance of all progenies.

• Its called prediction because its an estimation of the future performance of the animal’s offspring in relation to all progenies

EPD or PTA: Half of an individual’s breeding value (BV).

• A parent passes 1/2 of its BV to an offspring.

• The other half comes from the other parent

• On phenotypic selection the gain is determined by selection differential averaged for males and females

Estimated Breeding Value (EBV)

• Actual BV is unknown for most traits.

• We can estimate BV of an animal based on performance of the animal itself and its relatives.

• Similar to EPD, PTA, etc.

Estimating Breeding Value

Within Herd – Contemporary Group

Breeding Value Estimation

• Animal of Interest

– Animal whose BV is being estimated.

• Animal(s) of Record

– Animal(s) being evaluated or measured. Can be the animal of interest and(or) relatives.

Predicting Breeding Value

• Phenotypic deviation from a contemporary mean!!

• Population mean• Herd or flock mean• Mean of animal born in same management

group

• It’s a way to correct for non- genetic effects

Predicting Breeding Value Within Herd Genetic Evaluation

Standardization of Performance Records (WW205, YW365, SC365, REA480)

Adjustments(Age of the Cow, Age at weight data collection)


Population

FarmsContemporary

Groups

Within CGAdjustmentsAOD, Age…

Between CGReference Sires – Half Sibs


Table: Weaning weight adjustment factor for age of the dam.

Table: Birth weight adjustment factor for age of the dam.

AOD (yr) BIF

Bulls Heifers

2 60 54

3 40 36

4 20 18

.5-10 0 0

11+ 20 18

AOD (yr) BIF

Bulls Heifers

2 8 8

3 5 5

4 2 2

.5-10 0 0

11+ 3 3


Animal BW SEX AOD AdBW WW AGE WW205 YW AGE YW365

A 65 F 3 540 201 1050 368

B 80 M 7 610 199 1134 366

C 63 F 6 537 214 1038 381

D 74 F 8 580 223 1035 390

E 81 M 4 635 189 1194 356

F 71 M 12 610 193 1164 360

G 68 F 8 536 204 1070 371

H 75 M 5 614 207 1094 374

Example 1: Rank animals based on BW, WW205 and YW365



A 65 F 3 70 540 201 1050 368

B 80 M 7 80 610 199 1134 366

C 63 F 6 63 537 214 1038 381

D 74 F 8 74 580 223 1035 390

E 81 M 4 83 635 189 1194 356

F 71 M 12 74 610 193 1164 360

G 68 F 8 68 536 204 1070 371

H 75 M 5 75 614 207 1094 374


Rank for Males: F>H>B>E Rank for Females: C>G>A>D

Rank for BW



A 65 F 3 70 540 201 585.5 1050 368

B 80 M 7 80 610 199 626.0 1134 366

C 63 F 6 63 537 214 517.1 1038 381

D 74 F 8 74 580 223 539.2 1035 390

E 81 M 4 83 635 189 699.9 1194 356

F 71 M 12 74 610 193 679.5 1164 360

G 68 F 8 68 536 204 538.3 1070 371

H 75 M 5 75 614 207 608.8 1094 374



Rank for BW

Rank for Males: E>F>B>H Rank for Females: A>D>G>C

Rank for WW205



A 65 F 3 70 540 201 585.5 1050 368 1074.1

B 80 M 7 80 610 199 626.0 1134 366 1128.0

C 63 F 6 63 537 214 517.1 1038 381 997.1

D 74 F 8 74 580 223 539.2 1035 390 975.1

E 81 M 4 83 635 189 699.9 1194 356 1235.5

F 71 M 12 74 610 193 679.5 1164 360 1210.3

G 68 F 8 68 536 204 538.3 1070 371 1049.9

H 75 M 5 75 614 207 608.8 1094 374 1068.7



Rank for BW

Rank for Males: E>F>B>H Rank for Females: A>D>G>C

Rank for WW205

Rank for Males: E>F>B>H Rank for Females: A>G>C>D

Rank for YW365

Breeding Value (BV)

• The contribution of each effect is proportional to the variance explained

by effect

PV

VA

P

A

Additive Effect Dominance Environment

or Breeding Value

PV

VE

P

EPV

VD

P

d

• Concepts discussed on Phenotypic Selection still valid!!

Estimated Breeding Value (EBV)

• Notice that the Breeding Value of an animal is the sum of its genes Additive Effects

PV

VA

P

Aˆ

Additive Effect Breeding Value Genetic Gain

When estimated from Phenotypes Phenot. Selection

Phenotype expressed as

a deviation from the mean

PV

VBV

P

A ShG 2

• Concepts discussed on Phenotypic Selection still valid!!

General Formulas for BV and ACC

• P = trait mean of the animal(s) of record.

• trait mean of contemporary group.

• b = regression factor.

Phenotype expressed as a deviation from the mean

)( PPbBV

P

PV

VBV

P

A

Estimated Breeding Valuex

Expected Progeny Difference

EBVEPD2

1

• EPD = PTA = 1/2 EBV = the portion of an animal’s BV that is expected to be passed on to its progeny for a given trait.

Estimated Breeding Valuex

Expected Progeny Difference

EBVEPD2

1

What is the expected average Phenotype on the progeny (change on the distribution mean)

Accuracy (ACC) of EBV

• Mathematical expression of the degree of confidence that the EBV accurately predicts true BV.

• Ranges between 0 and 1.

General Formulas for EBV and ACC

• g = relationship weighting factor.

• b = regression factor.

gbACC

EBVEBVrACC

,

Correlation between real breeding value and estimated breeding value

i.e. the closest the estimation to real BV more accurate is the EBV

ACCURACYExpected Variation on Progeny

Difference

What is the expected average Phenotype on the progeny for high and low accuracy EPDs(change on the distribution mean)

Predicting Breeding Value Across-Herd Genetic Evaluation

Allows comparisons of breeding value estimates of animals in

different herds or contemporary groups.

Predicting Progeny Performance

• EBV = estimated breeding value (all species).

• EPD = expected progeny difference (beef, swine, and sheep).

• PTA = predicted transmitting ability (dairy).

To compare animals from different herds:

Must account for between-herd differences in:

1) environment

2) overall herd genetic potential (genetic potential of mates)

• Variation on mean contemporary group may be due environmental and genetic differences

• Question: How to differentiate Environmental and Genetic effects on different CG?


Must account for between-herd differences

in:

1) environment2) overall herd genetic potential(genetic

potential of mates)


Must account for between-herd differences in:

1) environment2) overall herd genetic potential(genetic potential of mates)

• 1) is accounted for by using sires in multiple herds simultaneously. See next slide.

• 2) relates to the fact that a sire used in a good herd will look better than when used in a bad herd because of the females he’s being mated to. Current statistical procedure account for this since all available records are used.

Reference sire concept

• Because of AI, a sire can produce progeny in multiple herds simultaneously.

• Such sires serve as a base or reference point in order to adjust for differences in E.

Across-Herd Genetic Evaluation

• Originally, genetic evaluation programs were based on within-herd comparisons only.

• Increased use of A.I. And more sophisticated computer programs allowed expansion to across-herd evaluation.

• Across-herd genetic evaluation programs are usually done separately by breed.


• Originally, in beef cattle, each breed with an across-herd evaluation program designated specific sires as reference sires. In order to have across-herd EPDs for animals in your herd, some of your calves had to be sired by reference sires.

• At that time, EPDs were calculated only for sires. Now they can be calculated for virtually every animal in the breed as long as the necessary trait data is available.

Herd 1 No. calves Avg WW % of bull A

Bull A 15 510 100.0

Bull B 12 480 94.1

Bull C 18 440 86.3

Herd 2

Bull A 12 540 100.0

Bull D 15 490 90.7

Bull E 12 480 88.9

Reference Sire concept

Reference Sire concept

Bull A is siring calves in both herds and so serves as a benchmark for comparisons.The column at the right compares each bull to Bull A in terms of progeny weaning weight.

If we used the WW column, we’d rank the bulls A - D - B,E - C. This would not be correct because Herd 2 has a better environment and (or) better cows.

Using the column at right, we correctly rank the bulls A - B - D - E - C.

This concept applies for other species as well.

Predicting Breeding Value Across-Herd Genetic Evaluation

Population

FarmsContemporary

Groups

Within CGAdjustmentsAOD, Age…

Between CGReference Sires – Half Sibs

Predicting Breeding Value

PopulationFarms

Contemporary Groups

Animals Compared within Contemporary Group.It’s a way to correct for non- genetic effects.

Reference Sires = Animal used in different contemporary groups or different farms.

Mean production of Half Sibs from Reference Sires allows the estimation of the effect of the contemporay group.

Once the contemporary group effect is calculated is possible to compare animals born in different farms.

Within Contemporary GroupAnimals have performance adjustedfor non-genetics effects such as age of the Dam

Reference Sire Concept

• Today, designated reference sires are not usually needed.

• Many sires serve as references without being designated as such.

• Other relationships between herds also serve as ties to adjust for differences in E.


• 1- Same animal in different herds (impossible for many traits)

• 2- Clones (not available)

• 3- Full Sibs (ET not very effective)

• 4- Half Sibs (AI – Improve connection between CG)

• 5- Any related animal (Connect different CGs)


• 1- Same animal in different herds (impossible for many traits)

• 2- Clones (not available)• 3- Full Sibs (ET not very effective)• 4- Half Sibs (AI – Improve connection between CG)• 5- Any related animal (Connect different CG)• Within family variation – number of progenies _____

• Mean of HS in different CG tend to be similar• n#HS < n# animals with more distant relationship.

Coefficient of Relationship

Beef Cattle EPDs

• Different programs for different breeds.

• National Sire Evaluation - previous.

• National Cattle Evaluation - today.

• Typical traits– Growth: BW, WW direct, YW, others.– Maternal: Milk, WW maternal.– Carcass: wt, external fat, REA, marbling.– Others: vary by breed

Breed Average EPD and $Values

BODY COMPOSITION $VALUES

%IMF RE Fat %RP $F $G $B

Current Sires1 0.02 0.08 0.002 0.01 11.7 12.2 23.8

Current Dams 1 0 0.01 0 0 4.21 12.2 18.2

Non-Parent Bulls 0.06 0.11 0.003 0.04 12.6 12.8 25.6

Non-Parent Cows 0.06 0.11 0.003 0.04 12 13.2 25.8

PRODUCTION CARCASS

BW WW Milk YW YH MW MH SC CW Marb RE Fat %RP

Current Sires1 2.6 36 18 66 1 4 0.8 0.2 4 0.11 0.120 0.001 0.07

Current Dams 1 2.7 30 15 55 1 0.1

Non-Parent Bulls 2.6 36 18 67 1 0.3

Non-Parent Cows 2.6 35 18 66 1

Genetic Base: 1979 Distributions

Interpretation

Yearling weight _

EPD, lb ACC

Bull A - 5.0 .56

Bull B +25.0 .72

Future offspring of B are expected to weigh 30 lb more than those of A at one year, on average.

Interpretation

Fat thickness _

EPD, in ACC

Bull A - .20 .41

Bull B + .08 .38

Offspring of A are expected, on average, to produce carcasses with .28 in less fat than those of B at the same slaughter age.

Beef Cattle EPDs

• Direct WW EPD: predicts WW difference of the animal’s own offspring (growth potential).

• Maternal WW EPD: predicts WW difference of calves of the animal’s daughters (milk and growth potential).

• Milk EPD: predicts the portion of WW difference of calves of the animal’s daughters due to milk (milk potential).

Beef Cattle EPDs

Direct WW Milk Maternal WW

Bull EPD ACC EPD ACC EPD ACC

A -2.0 .84 22.0 .72 21.0 .78

B 30.0 .73 -10.0 .65 5.0 .69

Maternal WW EPD = Milk EPD + 1/2 Direct WW EPD

Accuracy of EPD

• Similar to ACC of EBV.

• Level of confidence that the EPD closely approximates true PD.

• Is not a measure of expected variation among progeny.

• Use EPDs to select or rank breeding animals. Use ACC to determine how extensively an animal is used.

Accuracy and Associated Possible Change

•The following table lists the possible change values associated with each EPD trait at the various accuracy levels.

•Possible change is expressed as "+" or "-" pounds of EPD and can be described as a measure of expected change or potential deviation between the EPD and the "true" progeny difference.

•This confidence range depends on the standard error of prediction for an EPD. For a given accuracy, about two-thirds of the time an animal should have a "true" progeny difference within the range of the EPD plus or minus the possible change value.

More info higher Acc. (.3-.4 for young animals and .99 for sires with more than 500 offspring


•For example, a sire with an accuracy of .7 and birth weight EPD of +1.0 is expected to have his "true" progeny value falling within ±0.86 pounds for birth weight EPD (ranging between 0.14 and +1.86) about two-thirds of the time.

•With the conservative approach taken with respect to heritabilities in the Angus evaluation, actual EPD changes of animals within the population are much less than statistics would indicate.


Production EPD Carcass EPD Body Composition EPD

Acc BW WW Milk YW MW MH SC CW Marb RE Fat %RP %IMF RE Fat %RP

0.05 2.73 11.0 9.21 16.17 39.32 0.74 0.70 15.42 0.25 0.270 0.034 0.53 0.18 0.30 0.020 0.35

0.15 2.44 9.85 8.24 14.47 35.18 0.66 0.62 13.80 0.22 0.25 0.030 0.48 0.16 0.27 0.018 0.32

0.30 2.01 8.12 6.79 11.92 28.97 0.54 0.51 11.36 0.18 0.20 0.025 0.39 0.14 0.22 0.015 0.26

0.35 1.87 7.54 6.30 11.06 26.90 0.51 0.48 10.55 0.17 0.19 0.023 0.36 0.13 0.21 0.014 0.24

0.40 1.72 6.96 5.82 11.21 24.83 0.47 0.44 9.74 0.16 0.17 0.021 0.34 0.12 0.19 0.013 0.22

0.50 1.44 5.80 4.85 8.51 20.69 0.39 0.37 8.12 0.13 0.14 0.018 0.28 0.10 0.16 0.011 0.19

0.55 1.29 5.22 4.36 7.66 18.62 0.35 0.33 7.30 0.12 0.13 0.016 0.25 0.09 0.14 0.010 0.17

0.70 0.86 3.48 2.91 5.11 12.42 0.23 0.22 4.87 0.08 0.09 0.011 0.17 0.06 0.10 0.006 0.11

0.75 0.72 2.90 2.42 4.26 10.35 0.19 0.18 4.06 0.06 0.07 0.009 0.14 0.05 0.08 0.005 0.09

0.80 0.57 2.32 1.94 3.40 8.28 0.16 0.15 3.25 0.05 0.06 0.007 0.11 0.04 0.06 0.004 0.07

0.85 0.43 1.74 1.45 2.55 6.21 0.12 0.11 2.43 0.04 0.04 0.005 0.08 0.03 0.05 0.003 0.06

0.90 0.29 1.16 0.97 1.70 4.14 0.08 0.07 1.62 0.03 0.03 0.004 0.06 0.02 0.03 0.002 0.04

0.95 0.14 0.58 0.48 0.85 2.07 0.04 0.04 0.81 0.01 0.01 0.002 0.03 0.01 0.02 0.001 0.02

Variation on progeny (Distributions)


•For example, a sire with an accuracy of .7 and birth weight EPD of +1.0 is expected to have his "true" progeny value falling within ±0.86 pounds for birth weight EPD (ranging between 0.14 and +1.86) about two-thirds of the time.

•With the conservative approach taken with respect to heritabilities in the Angus evaluation, actual EPD changes of animals within the population are much less than statistics would indicate.

Beef Cattle EPDs

• Much information can be found on WWW.– Breed associations

• Angus - http://www.angus.org/index.html• Limousin - http://www.ansi.okstate.edu/breeds/cattle/limousin/• Hereford - http://www.hereford.org/tailored.aspx• Simmental – http://www.simmgene.com/

– A.I. Organizations• ABS Global - http://www.absglobal.com/home.html

http://www.angus.org/index.html

http://www.ansi.okstate.edu/breeds/cattle/limousin/



http://www.hereford.org/tailored.aspx

http://www.hereford.org/tailored.aspx

http://www.simmgene.com/

EPDs for commercial beef producers

• Unless using A.I., bulls will likely have low ACC values.

• Progeny of low ACC bulls tend to perform as expected when averaged over several bulls. Some individual bulls will be over- or under-estimated.

• The ACC of an EPD averaged over several bulls will be higher than the average of their individual ACCs.

Genetic Base

• Base = zero-point. EPDs calculated as deviations from “genetic base”.

• Fixed base example: all animals born 1979.

• Some breeds now use “floating base”.

• Implication: In general, an EPD of 0.0 does not equal current breed average.

Genetic Trends

-20

-10

0

10

20

30

40

1970 1975 1980 1985 1990 1995 2000 2005

Year

EPDs

BW

WW

Milk

CW

Marb

Across-breed EPDs

• In general, cannot compare EPDs computed by different breed associations.– Each breed conducts separate analysis.– Genetic base (zero-point) is different for

each breed.

• Table of across-breed adjustment factors from USDA MARC.

• Simmental uses some data from other breeds.

Across-breed EPDsADJUSTMENT FACTORS TO ADD TO EPDs OF FOURTEEN DIFFERENT BREEDS

TO ESTIMATE AB-EPDs

Breed Birth Weight Weaning Weight Yearling Weight Milk

Hereford 3.6 0.4 -8.8 -14.4

Angus 0 0 0 0

Shorthorn 7.4 28 39.1 13.1

South Devon 6.8 20.1 36 2.2

Brahman 13.1 34.1 -9.1 24.6

Simmental 6.8 20.7 18.1 13.2

Limousin 5.9 22.1 16.2 -1

Charolais 10.5 37.7 50.8 6

Maine Anjou 6.5 16 0.7 10.8

Gelbvieh 5.8 8.1 -19.9 13.1

Pinzgauer 7.6 26.1 21.3 7.2

Tarentaise 3.7 28.5 10.5 17.2

Salers 5.1 26.9 35.1 12.4

Red Angus 3.3 -4 -5.7 ---

National Sheep Improvement Program (NSIP)

• Across-flock EPDs are available for some animals in 6 breeds:– Columbia– Dorset– Hampshire– Polypay– Suffolk– Targhee

• Cannot compare EPDs between breeds

Sheep Maternal traits

• Number of lambs born per ewe lambing.

• Milk EPD.

• Milk + growth EPD =milk EPD + 1/2 (60-day wt EPD).

Sheep Growth traits

• Farm flocks– 60-day and 120-day weight

• Range flocks– 120-day and yearling weights

Sheep Wool traits.

• fleece weight (lb).

• fiber length (in).

• fiber diameter (microns).

Dairy Genetic Evaluation

• USDA computes across-herd values• Some animals are also included in an across-

country analysis (Interbull).• Predicted value is based on records from all

relatives.• Values are calculated as deviations from the

base.• The base for production traits was recently

updated to cows born in 1995.

Dairy Cattle Genetic Evaluation

• Production traits PTA = predicted transmitting ability (like EPD) PPA = predicted producing ability (like MPPA);

females only (repeatability).

• Type traits STA = standardized transmitting ability (standard

deviation units)

• REL = reliability (like ACC)

Production Traits

• PTA M (lb milk)

• PTA F (lb fat)

• PTA F% (% fat)

• PTA P (lb protein)

• PTA P% (% protein)

• PTA PL (productive life, months)

• PTA SCS (somatic cell score; lower better)

Dairy Linear (type) Traits

• Stature (height)

• Strength (frail vs. strong)

• Body depth

• Feet & leg score

• Udder traits

• Others

Dairy Management Traits

• Milking speed

• Temperament

• Non-return rate

Dairy Cattle

Milk Yield (305-day) _

PTA, lb RelBull A +1125 .66Bull B +2525 .92

Future daughters of B are expected to produce 1400 lb more milk per lactation than daughters of A, on average.

Dairy Cattle

Protein _

PTA, lb PTA, %

Bull C +58 - 0.05

Bull D +48 +0.04

Standard Indexes

• Net Merit

• Fluid Merit

• Cheese Merit

• TPI = type/production index

• Udder composite

• Feet & leg composite

14.1- Predicting Breeding Value 2

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